Machine Learning Specialization | Coursera

Explore the essentials of machine learning and develop practical skills to implement AI applications in this beginner-friendly program. Gain proficiency in a broad range of modern machine learning techniques such as supervised learning, unsupervised learning, neural networks, and decision trees, among others.

What you’ll learn
Build ML models with NumPy & scikit-learn, build & train supervised models for prediction & binary classification tasks (linear, logistic regression)
Build & train a neural network with TensorFlow to perform multi-class classification, & build & use decision trees & tree ensemble methods
Apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detection
Build recommender systems with a collaborative filtering approach & a content-based deep learning method & build a deep reinforcement learning model

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